Smart-phone bracket for car and truck navigation

ABSTRACT

Inertial navigation systems for wheeled vehicles with constrained motion degrees of freedom are described. Various parts of the navigation systems may be implemented in a smart-phone.

RELATED APPLICATIONS

This application is a continuation-in-part of U.S. patent applicationSer. No. 12/868,604 (“Cordless inertial vehicle navigation”) filed onAug. 25, 2010 and incorporated herein by reference.

TECHNICAL FIELD

The disclosure is generally related to inertial navigation systems forwheeled vehicles with constrained motion degrees of freedom.

BACKGROUND

Car and truck navigation systems based on global positioning system(GPS) receivers have become indispensable aids for both business andpleasure driving. Such systems do not work well, however, when signalsfrom GPS satellites are obscured or unavailable as may happen whendriving in a tunnel or urban canyon environment. To combat problems fromGPS signal loss, inertial measurement units (IMU) are combined with GPSreceivers to provide dead reckoning as a supplement to satellitenavigation.

Many of the hardware components necessary to implement a GPS+IMU systemare present in so-called “smart” sell phones, personal digitalassistants or tablet computers. We use “smart-phone” as short hand torefer to any of these kinds of devices. What is needed are systems andmethods to implement a GPS+IMU system for car or truck navigation takingadvantage of the display, processor and sensors found in typicalsmart-phone.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B show a wheeled vehicle that has yaw, longitudinalacceleration and rate-of-climb degrees of freedom.

FIG. 2 is a diagram showing geometric relationships associated withestimating speed with a longitudinal accelerometer and an altimeter.

FIG. 3 is a diagram showing geometric relationships associated witherrors that occur in measurements of longitudinal acceleration in aturning vehicle.

FIG. 4 is a block diagram of a cordless GPS+IMU system.

FIG. 5 is a flow diagram for operation modes of a cordless GPS+IMUsystem.

FIG. 6 shows an example of a smart-phone bracket for car and trucknavigation.

FIG. 7 shows an example of a smart-phone bracket for car and trucknavigation having wired connections for power and sensor input/output.

FIG. 8 shows an example of a smart-phone bracket for car and trucknavigation having wireless connections for sensor put/output

FIG. 9 shows an example of a smart-phone car and truck navigation systemhaving a wireless connection between a sensor unit and a smart-phone.

FIG. 10 is a block diagram of a GPS+IMU system implemented with asmart-phone and a smart-phone bracket in a car or truck.

DETAILED DESCRIPTION Introduction

U.S. patent application Ser. No. 12/868,604, “Cordless inertial vehiclenavigation” (filed on Aug. 25, 2010 and incorporated herein byreference) describes systems and methods for inexpensive GPS+IMUnavigation in cars and trucks. (“Cordless” refers to the elimination ofa connection to a vehicle's speedometer or tachometer.) Cars and truckspresent a special case because their motion is constrained and lateralacceleration, vertical acceleration and roll may all be ignored. Thedescription found in U.S. Ser. No. 12/868,604 is repeated below inPart 1. Cordless inertial vehicle navigation.

Smart-phones (including personal digital assistants and tabletcomputers) often include most (sometimes all) of the componentsnecessary to implement systems such as those described in Cordlessinertial vehicle navigation. Basic smart-phones may include a display,processor, memory, GPS receiver and accelerometer, for example. Moreadvanced models may include a gyroscope. In the near future smart-phonesmay even be equipped with pressure altimeters.

Although the systems described in Cordless inertial vehicle navigationare self-calibrating, they depend on the spatial relationship betweenmeasurement and body frames of reference being fixed. Thus thesmart-phone bracket for car and truck navigation described below (inPart 2: Smart-phone bracket for car and truck navigation) performs twobasic functions: (1) it provides a temporary, rigid attachment for asmart-phone to a vehicle; and, (2) it supplies sensors that may bemissing in the smart-phone.

A variation of the smart-phone bracket places all of the inertialsensors needed for car and truck navigation in a sensor unit that isfixed to a vehicle and communicates wirelessly with a smart-phone. Inthis case, the smart-phone is used for data processing and display, andis free to move about the cabin of the vehicle.

Part 1: Cordless Inertial Vehicle Navigation

One way to build a cordless GPS+IMU navigation system is to combinemeasurements from GPS, 3-axis rotation rate gyros and 3-axisaccelerometers in a Kalman filter or similar estimation algorithm. Suchsystems have been studied for decades and are routinely employed inaerospace navigation.

Practical difficulties arise, however, when cost is a significant designcriterion. Rate gyros and accelerometers based onmicro-electromechanical systems (MEMS) are attractive because of theircompact size and low cost. Unfortunately MEMS gyros build up milliradianlevel errors quickly. A one milliradian vertical error leads to a onecentimeter per second squared horizontal acceleration error—an effectthat quickly degrades positioning accuracy. Thus, a traditional GPS+IMUsystem design is not optimal for cars and trucks because of errors inlow-cost sensors.

A solution to the problem of building a low cost cordless GPS+IMUnavigation system having acceptable accuracy for cars and trucks dependsin part on recognition of constraints inherent in the typical motion ofthese vehicles. FIGS. 1A and 1B show a wheeled vehicle that has yaw,longitudinal acceleration and rate-of-climb degrees of freedom.

In FIG. 1, a wheeled vehicle 105, e.g. a car or truck, is shown in plan(A) and profile (B) views. The vehicle has four wheels, two of which arenot steerable (e.g. 110) and two of which are steerable (e.g. 115).(Wheeled vehicles may also have three, four or more wheels, one or moreof which may be steerable.) When the vehicle turns it yaws around apivot point 120 located approximately halfway between the non-steerablewheels. In FIG. 1B the vehicle is seen driving on a hill 125.

The vehicle shown in FIG. 1 has three degrees of freedom: yaw, ψ;longitudinal acceleration, A; and rate-of-climb, dh/dt. Motion of thevehicle is affected by a steering wheel that controls yaw rate, stop andgo pedals that control longitudinal acceleration, and by terrain, i.e.hills and valleys, that affect rate-of-climb. These motions may bemeasured with a yaw gyro, a longitudinal accelerometer and an altimeter,all of which may be MEMS devices.

It is not necessary to measure roll, lateral acceleration or verticalacceleration, and omitting such measurements eliminates the accumulationof their associated measurement errors. In cars, trucks and similarwheeled vehicles lateral acceleration is safely assumed to be equal tocentripetal acceleration. These sir simplifications are not applicableto bicycles and motorcycles (which do experience significant roll) orother unconstrained objects.

Given a vehicle with longitudinal acceleration and rate-of-climb degreesof freedom, dead reckoning based on a longitudinal accelerometer and analtimeter is one possible way to estimate speed. FIG. 2 is a diagramshowing geometric relationships associated with estimating speed in thismanner. In FIG. 2, a vehicle 205 (illustrated simply as a square block)is travelling on a slope 225. The angle of the slope with respect to thehorizon is θ, the height of the vehicle (above mean sea level or anyother convenlent reference plane) is h, and the speed of the vehicle onthe slope is v.

Inspection of FIG. 2 reveals that:

$\frac{v}{t} = {{A - {g\; \sin \; \theta \mspace{14mu} {and}\mspace{14mu} \sin \; \theta}} = {\frac{1}{v}\frac{h}{t}}}$

where g is the acceleration due to gravity near the surface of the earthand A is the longitudinal acceleration of the vehicle. Therefore,

$\frac{v}{t} = {A - {\frac{g}{v}\frac{h}{t}}}$

and thus speed may be estimated given measurements of longitudinalacceleration and height. A difficulty of this approach, however, is thesingularity at v=0. The cordless GPS+IMU navigation system describedhere avoids zero speed problems by adding a pitch gyro and combiningaltimeter, longitudinal accelerometer and pitch gyro measurements in aKalman filter.

The cordless GPS+IMU system is designed to be self calibrating such thatit may be placed in a vehicle without careful alignment of the MEMSgyros and accelerometer to the vehicle's axes. Self calibration is theprocess by which relationships between IMU, vehicle and earth-fixedreference frames are established.

The measurement reference frame M(x, y, z) is the frame in whichaccelerometer and rate gyro measurements are made. The vehicle or bodyreference frame B(f, r, d) [“forward”, “right”, “down”] is the framealigned with the axes of the vehicle in which the cordless GPS+IMUsystem operates. The earth-fixed reference frame E(E, N, U) [“East”,“North”, “Up”] is the frame of reference in which GPS measurements arereported.

Two examples of methods for self calibration are described. The first isblind calibration in which the orientation of body frame B is found interms of measurement frame M. The second is delta-V calibration in whichthe orientation of measurement frame M is found in terms of earth-fixedframe E, and the orientation of body frame B is also found in terms ofearth-fixed frame E. This information is then used to find theorientation of body frame B in terms of measurement frame M.

In blind calibration the direction of greatest acceleration (M frame)measured over a period of a few minutes lies along the vertical (yaw)axis (B frame). The direction along which changing acceleration (M) isobserved when yaw is near zero is the longitudinal (roll) axis (B).Filially, the lateral (pitch) axis (B) is perpendicular to the other twoaxes.

In delta-V calibration the orientation of measurement frame M is foundin terms of earth-fixed frame E by matching changes in velocitiesmeasured by IMU sensors and by GPS. Next, the orientation of body frameB is found in terms of earth-fixed frame E. Because of “rubber wheel”constraints, the B forward (“f”) direction is equal to the direction ofthe GPS (E frame) velocity at any moment. (Rubber wheel vehicles do notslide sideways.) The average (over a few minutes) B down (“d”) directionis parallel to the E frame up (“U”) direction. Finally, the lateral(pitch) axis (B) is perpendicular to the other two axes. Once M and Bare both known in terms of E, the relationship between M and B may bededuced.

Other calibration methods are possible. In general, the relationshipbetween the vertical axes of the body and measurement frames may bededuced from the direction of greatest acceleration (M frame) measuredover a period of a few minutes. This direction is parallel to thevertical (yaw) axis (B frame). The longitudinal (roll) axis (B frame)may then be determined by comparing accelerations measured by MEMSaccelerometers to accelerations determined from a history of positionmeasurements reported by a position sensor such as a GNSS receiver.

Yaw rate gyro measurements may be used to improve the accuracy oflongitudinal (roll) axis determination because lateral acceleration asmeasured by yaw rate multiplied by speed (ω_(ψ)v) is, in practice, moreaccurate than lateral acceleration determined by differencing GNSS speedmeasurements (Δv).

When a horizontal acceleration, A, is measured in both the M (x, y)frame (by accelerometers) and the B (f, r) frame (by GNSS speeddifferences), components A_(f), A_(r), A_(x) and A_(y) of theacceleration are related by:

$\begin{bmatrix}A_{f} \\A_{r}\end{bmatrix} = {\begin{bmatrix}{\cos \; c} & {\sin \; c} \\{{- \sin}\; c} & {\cos \; c}\end{bmatrix}\begin{bmatrix}A_{x} \\A_{y}\end{bmatrix}}$

where c is the constant angle that best satisfies the relationship overtime. Alternatively, the angle between the M and B frames in thehorizontal plane may be calculated as: a tan 2(A_(f), A_(r))−a tan2(A_(x) A_(y)).

A previously self-calibrated cordless GPS+IMU system may use calibrationinformation stored in memory to speed up self calibration procedures.Even after self calibration has determined the relative orientation ofthe M and B reference frames, the position of the cordless GPS+IMUsystem within a vehicle may affect IMU sensor measurements. For example,a horizontal acceleration error occurs during turns if a longitudinalaccelerometer is located away from the pivot point of a vehicle.

FIG. 3 is a diagram showing geometric relationships associated witherrors that occur in measurements of longitudinal acceleration in aturning vehicle. In FIG. 3 a wheeled vehicle 305, e.g. a car or truck,is shown executing a turn. The vehicle has non-steerable wheels (e.g.310) and steerable wheels (e.g. 315). The vehicle's pivot point 320 lieshalfway between the non-steerable wheels. A longitudinal accelerometeris represented by block 325; it is located a distance L ahead of thepivot point. (L is referred to as “accelerometer arm”, for lack of abetter term.) The radius of turn of the vehicle is R, the distance fromthe center of the turn 330 to the longitudinal accelerometer is r, andthe rate of turn (i.e. the vehicle's yaw rate) is ω_(ψ). The centrifugalforce at the accelerometer is ω_(ψ) ²r, and the longitudinal componentof this force, which is what is measured by the longitudinalaccelerometer, is

$\omega_{\psi}^{2}r{\left. \frac{L}{R} \right.\sim\omega_{\psi}^{2}}{L.}$

This error is removed in the cordless GPS+IMU navigation system bysubtracting ω_(ψ) ²L from longitudinal accelerometer measurements.

The cordless GPS+IMU navigation system thus operates under severalpractical constraints summarized in Table 1:

TABLE 1 GPS + IMU system constraints. Constraint Consequence Low-costMEMS sensors. Gyro and accelerometer measurement errors accumulatequickly. Wheeled vehicle (e.g. car or Lateral acceleration, verticaltruck). Lateral acceleration may acceleration and roll are ignored. beconsidered equal to centripetal No roll rate gyro needed. acceleration.Need to estimate both zero and Pitch rate, altimeter and non-zero speedsaccurately. longitudinal acceleration measurements are combined to avoidzero speed singularity. System may be placed in a System self-calibratessensors to vehicle without careful alignment establish relativeorientation of to vehicle axes. measurement and body frames ofreference. Longitudinal accelerometer may Longitudinal accelerometer bemounted away from vehicle measurements are corrected for pivot point.longitudinal component of centrifugal force in turns.

FIG. 4 is a block diagram of a cordless GPS+IMU system that operates inaccordance with all of the constraints of Table 1. In FIG. 4, MEMS pitchrate and yaw rate gyros 405, MEMS accelerometer 410, altimeter 415 andGPS receiver 420 all provide measurement inputs to navigation unit 425.The navigation unit contains a processor that uses a Kalman filter tocombine measurement inputs to estimate position, heading and speed. Thenavigation unit may be connected to an optional display 430. Thenavigation unit includes a memory which may contain map formation; themap information may be used for map-matching to improve positioningaccuracy on roads. The system may also include a wireless communicationunit to transmit vehicle position and speed information to others. Theentire cordless GPS+IMU system may be contained in a compact packagethat may be quickly and conveniently placed on a vehicle dashboard, forexample. The system may also be implemented in a personal digitalassistant, smart phone, or other general purpose device having thenecessary sensors.

MEMS, six-degree-of-freedom combination rate gyro and accelerometerunits are readily available at low cost. After self-calibrationprocedures described above, the output from one of these units may bemanipulated to create that of a virtual longitudinal accelerometer,pitch rate gyro and yaw rate gyro oriented in the B reference frame. Theconstraints of wheeled vehicles and low-cost MEMS sensors (see e.g. FIG.1 and Table 1) create a situation in which using only these threemeasurements (i.e. ignoring lateral and vertical acceleration, and roll)is preferable to using measurements along all six possible axes.

The navigation unit executes a Kalman filter to combine IMU and GPSmeasurements. The filter is arranged such that altimeter rate is themeasurement variable, and gyro and accelerometer measurements arecontrol variables that appear in the state dynamics equations. Vehiclespeed is determined through the combination of longitudinalacceleration, pitch rate and altimeter measurements. Some of the statevariables are measured by GPS when GPS signals are available. Lateralacceleration, vertical acceleration, and roll rate are not used in thefilter.

Kalman filter states, dynamics equations and measurement equations arepresented in Tables 2 through 5:

TABLE 2 Kalman filter state variables and dynamics equations. StateDescription State Variables State Dynamics Equations East E Ė = v sin γcos θ North N {dot over (N)} = v cos γ cos θ Up U {dot over (U)} = v sinθ Speed v {dot over (v)} = A − β_(A) + ν_(v) − g sin θ − ω_(Ψ) ²LHeading γ {dot over (γ)} = (ω_(Ψ) − β_(Ψ) + ν_(Ψ))/cos θ Pitch θ {dotover (θ)} = ω_(θ) − β_(θ) + ν_(θ) Accelerometer arm L {dot over (L)} = 0Accelerometer bias β_(A) {dot over (β)}_(A) = 0 + ν_(A) Yaw rate gyrobias β_(Ψ) {dot over (β)}_(Ψ) = 0 + ν_(Ψ) Pitch rate gyro bias β_(θ){dot over (β)}_(θ) = 0 + ν_(θ) Altimeter rate bias β_(h) {dot over(β)}_(h) = 0 + ν_(h)

TABLE 3 Kalman filter control variables. Control Description ControlVariables Yaw rate gyro ω_(Ψ) Control Variables measurement appear inPitch rate gyro ω_(θ) State Dynamics Equations measurement LongitudinalA accelerometer measurement

TABLE 4 Kalman filter measurement variable and measurement equation.Measurement Measurement Description Variable Measurement EquationAltimeter rate {dot over (h)} {dot over (h)} = v sin θ − β_(h) + ν_(h)

TABLE 5 Kalman filter GPS measurement variables and measurementequations. GPS GPS Measurement Measurement Description Variables GPSMeasurement Equations East E(GPS) E(GPS) = E_(GPS) + ν_(E) _(GPS) NorthN(GPS) N(GPS) = N_(GPS) + ν_(N) _(GPS) Speed v(GPS) v(GPS) = {squareroot over (Ė_(GPS) ² + {dot over (N)}_(GPS) ² + {dot over (U)}_(GPS)²)}+ ν_(v) _(GPS) Heading γ(GPS) γ(GPS) = atan(Ė_(GPS)/{dot over(N)}_(GPS)) + ν_(γ) _(GPS) Pitch θ(GPS) θ(GPS) = asin ({dot over(U)}_(GPS)/{dot over (v)}_(GPS)) + ν_(θ) _(GPS)

In Tables 2 through 5,

$\overset{.}{X} = {\frac{X}{t}.}$

β_(x) is the bias associated with variable X. Biases change over aperiod of minutes and may be affected, for example, by temperature.ν_(x) is the process noise associated with variable X. X(GPS) is statevariable X when GPS fix information is available. X_(GPS) is the valueof variable X as determined by GPS.

Table 2 lists state variables and their corresponding state dynamicsequations. When GPS signals are available, state variables E, N, U, v, γand θ are determined by GPS as presented in Table 5. When GPS signalsare not available, estimates for the state variables are updatedaccording to the dynamics equations.

Control variables, determined by IMU measurements, are presented inTable 3. The measurement variable (altimeter rate) and correspondingmeasurement equation are presented in Table 4.

If GPS pseudorange and Doppler measurements are used instead of computedGPS fixes, then GPS clock bias and frequency are included in Kalmanfilter state equations as presented in Table 6:

TABLE 6 Kalman fliter GPS state variables and dynamics equations. StateState State Description Variables Dynamics Equations GPS clock bias B{dot over (B)} = f GPS clock frequency f {dot over (f)} = 0 + ν_(f)

FIG. 5 is a flow diagram for operation modes of a cordless GPS+IMUsystem. The system self calibrates its sensors and provides positionheading and speed estimates based on GPS and/or IMU sensor measurements.

When the system awakes from being in an off state, the navigation unitself calibrates the IMU sensors. This may be done by retrieving the laststored state of the Kalman filter from memory and calibrating pitch, yawand altitude sensor biases based on stored information. If thenavigation unit is automatically turned on when a vehicle is turned on,it is often safe to assume that wake-up happens when the vehicle is notmoving, thus making recalibration simpler. Alternatively, or inaddition, calibration may be done using the blind and/or delta-Vtechniques described above.

If external position information from GPS is available (e.g. from GPS420), as is the case when several GPS satellites are in view, thenavigation unit uses GPS to estimate position, heading and speed, andalso to calibrate pitch, yaw, altitude and acceleration sensor biases.Accelerometer arm, L, is also estimated. Optionally, an initial valuefor L may be input manually.

If external position information is not available, as is the case whendriving in a tunnel, for example, the navigation unit uses stored sensorbias information and pitch, yaw, altitude and acceleration sensormeasurements to update estimated position, heading and speed.

In conclusion, a cordless GPS+IMU navigation system has been described.The system uses three sensors (pitch rate, altitude and longitudinalacceleration) to estimate speed in the absence of GPS input. The systemis self calibrating and corrects for errors due to distance away fromthe yaw axis of a vehicle. The entire system may be contained in acompact package that may be quickly and conveniently mounted in avehicle without the need for careful alignment with vehicle axes. Thesystem may also be implemented in a personal digital assistant, smartphone, or other general purpose device having the necessary sensors.

Although the disclosure has discussed satellite based navigation interms of GPS receivers, clearly other global navigation satellite system(GLASS) (e.g. GLONASS, Galileo Compass, etc.) receivers may be usedinstead of, or in combination with, GPS.

Part 2: Smart-Phone Bracket for Car and Truck Navigation

As discussed above, a GPS+IMU system for cars and trucks uses yaw-rateand pitch-rate gyros, a longitudinal accelerometer, an altimeter and aGPS receiver. Many smart-phones contain accelerometers and GPSreceivers. Some also include gyros, and a few have altimeters. All ofthem have processors, memory, displays and wireless communicationcapability. Thus, a GPS+IMU system may be implemented in a smart-phoneif missing sensor measurements (if any) are made available.

It is possible, in theory, to keep track of a smart-phone's location andorientation using inertial sensor data. In practice, however, sensorerrors accumulate rapidly and positioning accuracy quickly degrades. Forcar and truck navigation, the limitations Inherent in the cheap (usuallyMEMS) inertial sensors found in smart-phones may be overcome byrecognizing that the motion of a vehicle driving on a road isconstrained. Lateral acceleration, vertical acceleration and roll mayall be ignored.

To take advantage of the constrained motion of a vehicle, the sensorsused in vehicle navigation must be fixed with respect to the vehicle.The motion of a smart-phone held in a person's hand, perhaps wavingaround, inside a car is far more complex than the motion of the caritself. Thus a smart-phone bracket provides a temporary, rigidattachment between a smart-phone and a vehicle so that sensors in thesmart-phone sense vehicle motion rather than arbitrary motion.

FIG. 6 shows an example of a smart-phone bracket for car and trucknavigation. Bracket 605 holds smart-phone 610. In FIG. 6, the bracket isattached to the dashboard of a car; however, the bracket could beattached to any other part of the car. The bracket may be attached tothe inside of the windshield by a suction cup, for example; or it may bedesigned to mate with air vents, cup holders, a rear-view mirror,steering column, etc. Mechanically, the function of the bracket is toprevent relative motion between the smart phone that it holds and thevehicle to which it is attached. A wide variety of brackets withsuitable mechanical properties are readily available; however,conventional brackets do not include sensors for vehicle navigation.

FIG. 7 shows an example of a smart-phone bracket for car and trucknavigation having wired connections for power and sensor input/output.In FIG. 7, bracket 705 holds smart-phone 710. Bracket 705 includessensors such as an altimeter or rate gyro. Communications between thesensor(s) and the smart-phone are carried by a wire 715 that plugs intothe smart-phone. Wire 715 may also carry electrical power from thebracket to the smart-phone or vice versa. (Wire 715 may include anynumber of conductors as needed for data and power transmission.)Optional wire 720 connects the bracket to a vehicle power source such asa cigarette lighter socket.

Many variations are possible in the system of FIG. 7. The sensors inbracket 705 may include any of: accelerometers, gyros, GPS receiver, oraltimeter. Usually the bracket supplies sensors that are not included ina smart-phone with the most common example being an altimeter.

Bracket 705 may obtain power from a vehicle; e.g. via optional wire 720.The bracket may then supply power to its sensors, to a smart-phone, orto both. Wire 715 may supply power to a smart-phone or take power from asmart-phone to power sensors in the bracket.

Wire 715 provides data communications between sensors in the bracket anda processor in a smart-phone. The data may be carried over a serialport. Data and power may also be carried to and from a smart-phone asaudio frequency electrical signals. A smart-phone's audio input andoutput provide convenient analog-to-digital and digital-to-analoginterfaces for transmitting kilohertz-rate data. The audio output mayalso provide several milliwatts of power.

FIG. 8 shows an example of a smart-phone bracket for car and trucknavigation having wireless connections for sensor input/output. In FIG.8, bracket 805 holds smart-phone 810. Bracket 805 includes sensors suchas an altimeter or rate gyro. Communications between the sensor(s) andthe smart-phone are transmitted wirelessly, for example using Bluetooth,ZigBee or Wi-Fi. An optional wire 820 connects the bracket to a vehiclepower source.

The sensors in bracket 805 may include any of: accelerometers, gyros,GPS receiver, or altimeter. Usually the bracket supplies sensors thatare not included in a smart-phone with the most common example being analtimeter. In the special case that a bracket provides all of theinertial sensors required for GPS+IMU car or truck navigation, therequirement to fix the orientation of the smart-phone with respect tothe vehicle is removed. In this case the smart-phone provides aprocessor, memory and display which need not remain fixed inside avehicle.

FIG. 9 shows an example of a smart-phone car and truck navigation systemhaving a wireless connection between a sensor unit and a smart-phone. InFIG. 9, sensor unit 905 communicates wirelessly with smart-phone 910.Sensor unit 905 is fixed to a vehicle and contains all of the inertialsensors necessary for GPS+IMU vehicle navigation: accelerometers, gyrosand an altimeter. Smart-phone 910 contains a processor, memory anddisplay. A GPS receiver may be included in sensor unit 905 orsmart-phone 910. If smart-phone 910 contains a GPS receiver, then sensorunit 905 may be mounted in a vehicle without regard for whether or notGPS satellites are visible.

FIG. 10 is a block diagram of a GPS+IMU system implemented with asmart-phone and a smart-phone bracket in a car or truck. In FIG. 10,bracket or sensor unit 1005 may communicate with smart-phone 1010 viawired or wireless data and/or power link 1025. Optional vehicle power1015 is supplied to bracket or sensor unit 1005 and/or smart-phone 1010via wired power links 1020 and 1030, respectively.

Smart-phone 1010 may be an advanced cell phone, a personal digitalassistant, a tablet computer, or similar device. It need not include acellular telephone. Smart-phone 1010 includes a display, a processor,memory, one or more optional sensors, data input and/or output ports,and wireless communications. Sensors in smart-phone 1010 may include aGPS receiver, an accelerometer, a rate-gyro, and an altimeter. Theaccelerometer and rate gyro may perform measurements along threeorthogonal axes. Wireless communications in smart-phone 1010 may includecellular telephone, Bluetooth, Wi-Fi, Wi-Max, or other communicationstechnologies.

Bracket or sensor unit 1005 may contain one or more inertial sensors,data input and/or output ports, an optional power supply and optionalwireless communications. Clearly, if optional data link 1025 is awireless link, then bracket or sensor unit 1005 must include wirelesscommunications capability.

The overall system depicted in FIG. 10 requires accelerometer and gyroinertial sensors, an altimeter and a GPS receiver; however, thesesensors may be included in various combinations in the bracket or sensorunit and the smart-phone. The smart-phone may communicate with outsidedata sources via the internet or a private data network to obtaininformation such as map data, traffic, weather nearby attractions, etc.

Smart-phones that include all necessary sensors for GPS+IMU navigationmay use a bracket solely to provide a temporary, rigid attachment to avehicle. In this case, the smart-phone executes software instructions toestimate position, heading and speed of the vehicle based on thesmart-phone's own GPS and inertial sensors, and using the methodsdescribed above. To provide accurate position, heading and speedestimates the smart-phone detects when it is being securely held in itsbracket by any of a number of different indications.

Perhaps the simplest indication that a smart-phone may use to determinethat it is held in a bracket is an explicit instruction from a user. Forexample, a user may press a button, touch a screen, use gesture basedinputs like shaking, waving or tapping, or use voice commands toindicate that the smart-phone should commence GPS+IMU navigation.Alternatively, the smart-phone may identify a bracket by detectingmagnets, physical indentations, RHID tags, near-field communicationsdevices, or other identifying bracket characteristics.

CONCLUSION

As one skilled in the art will readily appreciate from the disclosure ofthe embodiments herein, processes, machines, manufacture, means,methods, or steps, presently existing or later to be developed thatperform substantially the same function or achieve substantially thesame result as the corresponding embodiments described herein may beutilized according to the present invention. Accordingly, the appendedclaims are intended to include within their scope such processes,machines, manufacture, means, methods, or steps.

The above description of illustrated embodiments of the systems andmethods is not intended to be exhaustive or to limit the systems andmethods to the precise form disclosed. While specific embodiments of,and examples for, the systems and methods are described herein forillustrative purposes, various equivalent modifications are possiblewithin the scope of the systems and methods, as those skilled in therelevant art will recognize. The teachings of the systems and methodsprovided herein can be applied to other systems and methods, not onlyfor the systems and methods described above.

In general, in the following claims, the terms used should not beconstrued to limit the systems and methods to the specific embodimentsdisclosed in the specification and the claims, but should be construedto include all systems that operate under the claims. Accordingly, thesystems and methods are not limited by the disclosure, but instead thescope of the systems and methods are to be determined entirely by theclaims.

What is claimed is:
 1. A navigation system comprising: a bracket forrigidly attaching a smart-phone to a car or truck, the bracketcomprising: an altimeter for providing altitude data to the smart-phone.2. The system of claim 1, the altimeter comprising a MEMS pressuresensor.
 3. The system of claim 1 further comprising: a wire forconnecting the bracket and the smart-phone, the wire capable oftransmitting sensor data.
 4. The system of claim 1 further comprising: awire for connecting the bracket and the smart-phone, the wire capable oftransmitting electrical power.
 5. The system of claim 1 furthercomprising: a wireless system for transmitting data between the bracketand the smart-phone.
 6. The system of claim 1 further comprising: a wirefor connecting the bracket and the car or truck, the wire capable oftransmitting electrical power.
 7. The system of claim 1, the bracketfurther comprising: a pitch rate gyro and a yaw rate gyro.
 8. The systemof claim 7, the pitch rate and yaw rate gyros being MEMS gyros.
 9. Thesystem of claim 1, the bracket further comprising: a longitudinalaccelerometer.
 10. The system of claim 9, the longitudinal accelerometerbeing a MEMS accelerometer.
 11. The system of claim 1, the bracketfurther comprising: a GNSS receiver.
 12. The system of claim 1, thesmart-phone being a tablet computer.
 13. A navigation system comprising:a sensor unit capable of being rigidly attached to a car or truck, thesensor unit comprising: an altimeter, a pitch rate gyro and yaw rategyro, a longitudinal accelerometer, and a wireless system for sendingsensor data to a smart-phone.
 14. The system of claim 13, the sensorunit further comprising a GNSS receiver.
 15. The system of claim 13, thealtimeter comprising a MEMS pressure sensor.
 16. The system of claim 13,the pitch rate and yaw rate gyros being MEMS gyros.
 17. The system ofclaim 13, the longitudinal accelerometer being a MEMS accelerometer. 18.The system of claim 13 further comprising: a wire for connecting thesensor unit to the car or truck, the wire capable of transmittingelectrical power.
 19. The system of claim 13, the smart-phone being atablet computer.
 20. A computer-readable medium having instructionsstored thereon that when executed cause a method for estimatingposition, heading and speed of a wheeled vehicle to be performed, themethod comprising: executing Kalman filter in a processor to estimateposition, heading and speed based on: altitude, pitch rate, yaw rate andlongitudinal acceleration information from an altimeter, pitch rategyro, yaw rate gyro and longitudinal accelerometer, respectively, andposition information from a position sensor when position information isavailable; wherein, the Kalman filter does not require lateralacceleration, vertical acceleration or roll rate.